The help tutor: does metacognitive feedback improve students' help-seeking actions, skills and learning?

  • Authors:

  • Ido Roll;Vincent Aleven;Bruce M. McLaren;Eunjeong Ryu;Ryan S. J. d. Baker;Kenneth R. Koedinger

  • Affiliations:

  • Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA;Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA;Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA;Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA;Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA;Human Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
  • Year:
  • 2006

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Abstract

Students often use available help facilities in an unproductive fashion. To improve students' help-seeking behavior we built the Help Tutor – a domain-independent agent that can be added as an adjunct to Cognitive Tutors. Rather than making help-seeking decisions for the students, the Help Tutor teaches better help-seeking skills by tracing students actions on a (meta)cognitive help-seeking model and giving students appropriate feedback. In a classroom evaluation the Help Tutor captured help-seeking errors that were associated with poorer learning and with poorer declarative and procedural knowledge of help seeking. Also, students performed less help-seeking errors while working with the Help Tutor. However, we did not find evidence that they learned the intended help-seeking skills, or learned the domain knowledge better. A new version of the tutor that includes a self-assessment component and explicit help-seeking instruction, complementary to the metacognitive feedback, is now being evaluated.